The man lay motionless in a car parked just outside a Cincinnati, OH fire station. It was a muggy Friday morning last September. According to local news, the man’s friend banged on the firehouse door, trying to get paramedics’ attention. She told them he had overdosed on heroin.

Cincinnati’s paramedics had spent the week racing around the city responding to overdoses, knowing minutes could spell the difference between life and death. They had already delivered at least 74 doses of overdose-reversal medication amidst the second wave of an “unprecedented" surge in cases. All that surprised them about the morning’s victim was that he had appeared on their doorstep.

City officials nationwide are scrambling to respond, devising novel strategies to mitigate residents’ suffering and manage scarce public resources. In these efforts, the smartest cities have sought out data that has helped them understand and confront their unique drug problems.

For this piece, I reviewed two data-driven strategies that have generated traction for locally-sourced interventions: New York City’s interagency RxStat initiative and Cincinnati’s open data approach. Next, I conducted original analysis using examples of datasets that have been central to each strategy. These are datasets that any city can readily obtain or can begin generating immediately. Here, in two parts, are examples of organizational strategies and analytic methods that could help guide effective municipal responses to the overdose crisis.

New York, NY: “The data brings everybody together”

Before RxStat, which grew out of a mayoral task force on prescription painkiller abuse in 2012, New York City had no formal system for monitoring drug overdoses. Today, representatives from public health and public safety agencies meet monthly to review recent data from diverse sources including medical examiner reports, drug-related prosecutions, and jail intake records. Inspired by the New York Police Department’s (NYPD) CompStat program for reviewing crime patterns and tailoring strategies accordingly, RxStat helps coordinate the city’s response to its latest safety crisis: while deaths from homicide and motor vehicle accidents trend downward, drug overdose deaths have more than doubled since 2009.

From the effort’s early days, when agencies understood little about the city’s overdose problem, RxStat has evolved to generate actionable information and shape city policy, said Denise Paone, an RxStat principal and director of research and surveillance for the Department of Health and Mental Hygiene’s drug and alcohol bureau. For example, RxStat helped incorporate drug overdoses into the data analytics system that monitors reports from city emergency rooms. When the system caught a cluster of overdoses in North Bronx emergency rooms, the health department sent a rapid assessment team to investigate. The team identified a lack of resources among local service agencies, so the department provided naloxone (Narcan) training and 1200 kits.

Perhaps most importantly, data analysis aids collaboration among public health and public safety agencies, which do not routinely work together. Useful information stimulates officials’ curiosity, said Daliah Heller, a former assistant commissioner in the health department who helped launch RxStat. “You can’t just make everyone sit in a room. The data brings everyone together.”

Heller described how the initiative began with data that was readily accessible to the health department but which not every agency had seen, such as mortality data derived from medical examiners’ reports. For law enforcement, this dataset offered a new window into drug usage patterns. For instance, the reports—examples of which I analyze below—can indicate how many fatal overdoses involve misuse of prescription opioids, like oxycodone, versus street drugs like heroin.

The data also allowed New York City agencies to rally around a primary goal of reducing overdose deaths citywide. With some jurisdictions considering harsh responses towards drug users and drug sellers, this single indicator can help focus attention on the need for strategies that emphasize harm reduction over retribution. In New York City, the goal of reducing overdose deaths prompted a tactical shift in law enforcement: NYPD, for example, is now advertising that bystanders can call 911 to report overdoses without being arrested, has begun diverting arrestees to drug treatment, and equipped cops with naloxone.

These are strategies aimed at reducing deaths, not making arrests and seizures. “The key lesson that we have learned from CompStat is that ‘what gets measured gets done,’” explained Chauncey Parker, a New York County prosecutor and RxStat principal. “So if the goal is to reduce overdoses, then overdoses will go down.”

Mortality data: the ‘who’ and ‘what’ of local epidemics

In addition to providing an outcomes indicator—total overdose deaths—mortality records can help understand local overdose epidemics. For public health practitioners, reports from medical examiners represent “vital statistics” on population health trends. For law enforcement, however, medical examiners’ rulings are most often relevant to the investigation of individual cases. It is not surprising, then, that until 2012 the NYPD—a famously data-oriented municipal police department, and America’s largest—was not routinely monitoring death data for citywide trends relevant to the opioid epidemic. Those records were one of the first datasets RxStat coordinators used to bring partners to the table.

According to public health maxim, the first step in an outbreak is to “know your epidemic.” Data on accidental drug poisonings (i.e., overdoses) typically includes one record for each decedent, with demographic characteristics (age, gender, and race), place of residence and location of death, a listing of drugs identified by toxicology tests, and an assessment of the specific cause of death. (For examples of medical examiners’ records, readers can see open data versions from Connecticut and Allegheny County, PA, analyzed below.) Policymakers can use mortality data to understand demographic patterns among overdose victims and to spot broad trends in where and when deaths occur.

The records may be most valuable, however, for their detailed information on the mix of substances used by overdose victims. In this section I illustrate how this data can drive analyses that are policy-relevant for all agencies.

“We have a fentanyl problem”

In jurisdictions with high death rates, there is no issue more salient than the role of fentanyl, and no source more important than medical examiner’s reports for understanding its impact. Fentanyl is a synthetic opioid 30 to 50 times stronger than heroin, approved for pain treatment but often manufactured and shipped with illicit use in mind. Agencies like the Centers for Disease Control and Prevention (CDC) had already acknowledged an overdose epidemic based on data from 2014 and earlier. But since then, many jurisdictions’ overdose death rates have soared even further, primarily because of fentanyl.

For example, in Allegheny County, which includes the City of Pittsburgh, deaths have nearly tripled since 2014. Even heroin’s role has waned as fentanyl has dominated causes of death.

Similarly, in Connecticut, what was once a widespread heroin epidemic has become, at least equally, a fentanyl epidemic.

Reflecting on similar figures from Manchester, NH, the city’s fire chief told U.S. News & World Report, “We don’t have a heroin problem here, we have a fentanyl problem.”

Fentanyl is cheaper than heroin, easy to transport because of its potency, and simple to mix into white powder heroin, cocaine or other substances. Paramedics report that many doses of naloxone may be necessary to revive an overdose involving fentanyl—if they work at all. Contact with fentanyl poses a bodily threat to first responders who might encounter it: the Drug Enforcement Agency issued a safety guide following the overdose of a Ohio police officer who had merely brushed fentanyl powder off his uniform.

Medical examiners were early to notice an important emerging trend: an increase in overdoses involving both cocaine and fentanyl without heroin present, suggesting that street cocaine might have been laced with fentanyl. In Allegheny County, two waves of the fentanyl epidemic are visible: until last summer, most decedents who had consumed fentanyl had also consumed heroin. Thereafter, fentanyl-heroin combination deaths decline and fentanyl-only overdoses become the single most common type.

Meanwhile, fentanyl-cocaine overdoses increased as well. While those decedents might have consumed each drug separately, investigators in New York City reported laboratory confirmation that fentanyl-laced cocaine has been found in circulation. In Cuyahoga County, OH, the chief medical examiner has alleged that drug retailers are targeting African-American drug users in the Cleveland area by adding fentanyl to cocaine, which is more popular than heroin among black residents. Indeed, in nearby Allegheny County, around 30% of decedents from fentanyl-cocaine combinations, without heroin, are black, similar to the proportion of decedents from cocaine-only overdoses. In contrast, the number of black victims from all other substance combinations is roughly proportional to the county’s black population, around 12%.

To assess local conditions, officials can consult death records. For example, New Haven, CT, experienced at least two fentanyl-cocaine overdoses last June from a batch of fentanyl-laced cocaine that prompted a rapid interagency response when 12 overdose patients hit the Yale New Haven Hospital emergency room in an eight-hour span. Local media covered the case against the drug seller, who received a seven-year sentence for selling the batch after he had overdosed himself using it. However, according to medical examiner’s reports, four more fentanyl-cocaine overdose deaths happened in New Haven after June—and I could not find media reports for any of them.

Powerful, but slow and small

For situational awareness, medical examiners’ records suffer two major limitations. The first is timeliness. It takes time for pathologists to review each case and publish their findings. Even in the best-equipped jurisdictions, like New York City, the data includes a two-to-three month time lag; in others, particularly with overdose deaths surging, lags might stretch to a year or longer. Using this data to guide actions is therefore “like driving while looking in the rearview mirror,” as Juan Colon, the intelligence chief for the New Jersey State Police, put it to a police forum [PDF].

Equally important, they may not include enough records to identify meaningful patterns, especially for smaller cities experiencing fewer overdose deaths. More sophisticated analyses require dozens, if not hundreds, of incidents for statistical power. For example, attempts to identify overdose “hot spots” using small datasets are as likely to mislead as to provide insight.

Convening against overdoses

Despite these limitations, every official confronting the overdose epidemic must understand local mortality patterns and trends. Every city must understand the scope of its current fentanyl problem and anticipate increased burden, including the dose of naloxone required to revive victims of fentanyl overdoses: in New Haven’s incident, for example, reviving some victims required 20 to 40 times the standard initial dose. Officials should use the data to look for evidence of emerging issues like fentanyl-laced cocaine and rising deaths in communities of color.

Moveover, these records could provide the starting point for interagency collaborations like New York City’s RxStat. Unlike some other public health datasets, mortality data is typically easy to obtain and share within government. With some basic analysis, it is simple to interpret. While this data cannot provide every answer (and should not be compared across jurisdictions due to reporting differences), it can raise important questions and prompt conversations across disciplines. For a listing of the medical examiner’s codes necessarily to identify accidental overdoses, and to find other datasets that local task forces can consult, the RxStat team’s technical manual [PDF] details the sources they have used in their own work.